Angle independent velocity spectrum determination

ABSTRACT

An ultrasound imaging system ( 100 ) includes a transducer array ( 102 ) that emits an ultrasound beam and produces at least one transverse pulse-echo field that oscillates in a direction transverse to the emitted ultrasound beam and that receive echoes produced in response thereto and a spectral velocity estimator ( 110 ) that determines a velocity spectrum for flowing structure, which flows at an angle of 90 degrees and flows at angles less than 90 degrees with respect to the emitted ultrasound beam, based on the received echoes.

RELATED APPLICATION

This application is a national filing of PCT application Serial No.PCT/IB2012/002527, filed Nov. 28, 2012, published as WO2014/083373 onJun. 5, 2014. This application claims priority to PCT application SerialNo. PCT/IB2012/002527, published as WO2014/083373 on Jun. 5, 2014.

TECHNICAL FIELD

The following relates to angle independent velocity spectrumdetermination and is described with particular application to ultrasoundimaging.

BACKGROUND

An ultrasound scanner has been used to estimate a velocity spectrum forflowing structure in an object or subject of interest at a given depthand visually present the velocity distribution as a function of time ina spectrogram. The spectrogram has been calculated by measuring asampled signal at the given depth and then employing a Fourier transformon the received data. This is discussed in Baker, “Pulsed ultrasonicDoppler blood-flow sensing,” IEEE Trans. Son. Ultrason., SU-17:170-185(1970), Evans et al., “Doppler Ultrasound, Physics, Instrumentation, andClinical Applications: John Wiley & Sons, New York (1989), and Jensen,“Estimation of Blood Velocities Using Ultrasound: A Signal ProcessingApproach,” Cambridge University Press, New York (1996).

For the display, the spectra are stacked side-by-side to show the timeevolution of the velocity distribution. The relation between thevelocity of the flowing structure and the measured frequency (f_(p)) canbe represented as shown in EQUATION 1:

$\begin{matrix}{{f_{p} = {{\frac{2\; v_{z}}{c}f_{0}} = {\frac{2{\overset{\rightarrow}{v}}\cos\;\Theta}{c}f_{0}}}},} & {{EQUATION}\mspace{14mu} 1}\end{matrix}$where f₀ is the frequency of the emitted ultrasound beam, c is the speedof sound, v_(z) is the structure velocity in the axial direction, and Θis the angle between the structure velocity vector and the ultrasoundbeam. With this approach, only the axial velocity component is measured,and this measurement should be corrected for the angle Θ. However, whenΘ=90 degrees, cos Θ=0, no velocity can be found. As such, this approachcannot be used for measuring velocity in vessels that are transverse tothe ultrasound beam direction.

SUMMARY

Aspects of the application address the above matters, and others.

In one aspect, an ultrasound imaging system includes a transducer arraythat emits an ultrasound beam and produces at least one transversepulse-echo field that oscillates in a direction transverse to theemitted ultrasound beam and that receive echoes produced in responsethereto and a velocity processor that determines a velocity spectrum forflowing structure, which flows at an angle of 90 degrees and flows atangles less than 90 degrees with respect to the emitted ultrasound beam,based on the received echoes.

In another aspect, a method includes receiving echoes in response toemitting an ultrasound beam and at least one transverse pulse-echo fieldthat oscillates in a direction transverse to the emitted ultrasound beamand determining a velocity spectrum for flowing structure, which flowsat an angle of 90 degrees and flows at angles less than 90 degrees withrespect to the emitted ultrasound beam, based on the received echoes.

In another aspect, a velocity processor includes a first spectralvelocity estimator that estimates spectral velocity components inresponse to an angle between a velocity vector and the ultrasound beambeing less than a first threshold angle, which does not include ninetydegrees, wherein the first spectral velocity estimator estimates thespectral velocity components based on a measured frequency and a secondspectral velocity estimator that estimates spectral velocity componentsin response to the angle between the velocity vector and the ultrasoundbeam being greater than the first threshold angle, which include ninetydegrees, wherein the second spectral velocity estimator estimates thespectral velocity components based on a correlation of the receivedechoes.

Those skilled in the art will recognize still other aspects of thepresent application upon reading and understanding the attacheddescription.

BRIEF DESCRIPTION OF THE DRAWINGS

The application is illustrated by way of example and not limited by thefigures of the accompanying drawings, in which like references indicatesimilar elements and in which:

FIG. 1 illustrates an example ultrasound imaging scanner that includes aspectral velocity estimator with a first spectral velocity estimator anda second spectral velocity estimator, which estimates spectralvelocities, even where the angle between the velocity vector of thestructure and the ultrasound beam is ninety degrees.

FIG. 2 illustrates an example of the first spectral velocity estimatorwhich determines a spectral velocity based on emitted ultrasound beamfrequency and a measured frequency;

FIG. 3 illustrates an example of the second spectral velocity estimatorwhich determines a spectral velocity based on a second order approach;

FIG. 4 illustrates an example of the second spectral velocity estimatorwhich determines a spectral velocity based on a fourth order approach;

FIG. 5 illustrates a method in accordance with the spectral velocityestimator embodiments disclosed herein.

DETAILED DESCRIPTION

FIG. 1 schematically illustrates an example ultrasound imaging system100.

The ultrasound imaging system 100 includes a transducer array 102 withan array of transducer elements 103, which are configured to transmitultrasound signals and receive echo signals. In one non-limitinginstance, the array of transducer elements 103 is a 1D array with 64,192, etc. elements. In another instance, the array of transducerelements 103 is a 2D array with 32×32, 64×64, etc. elements. It is to beappreciated that the 1D and/or 2D arrays of transducer elements 103 caninclude more or less elements. Furthermore, the transducer array 102 canbe linear, curved, and/or otherwise shaped, and/or fully populatedand/or sparse.

Transmit circuitry 104 generates pulses that excite a predetermined setof the transducer elements 103 to emit one or more ultrasound beams intoa scan field of view, and receive circuitry 106 receives echoesgenerated in response to the transmitted ultrasound beams interactingwith (generally stationary and/or flowing) structure in the scan fieldof view. In one instance, the transmit circuitry 104 is operated so thatan axial pulse-echo field oscillates in the axial direction along theaxis of the emitted ultrasound beam and at least one lateral ortransverse (i.e., azimuth and/or elevation) pulse-echo field oscillatesin a transverse direction, which is generally perpendicular to theemitted ultrasound beam, and different sets of elements 103 (e.g., setsof thirty-two (32) elements, etc.) receive echoes corresponding to thedifferent pulse-echo fields.

Operation of the transmit circuitry 104 and the receive circuitry 106,as discussed in the preceding paragraph, with respect to emittingmultiple different oscillation fields that are transverse to each other,can be achieved using the transverse oscillation (TO) approach. The TOapproach with respect to the axial and one transverse directions isdiscussed in J. A. Jensen and P. Munk, “A New Method for Estimation ofVelocity Vectors,” IEEE Trans. Ultrason., Ferroelec., Freq. Contr., vol.45, pp. 837-851 (1998), J. Udesen and J. A. Jensen, “Investigation ofTransverse Oscillation Method,” IEEE Trans. Ultrason., Ferroelec., Freq.Contr., vol. 53, pp. 959-971 (2006), EP19970928135, titled “Apparatusand Method for Determining Movement and Velocities of Moving Objects,”and WO/2000/068678A1, title “Estimation of vector velocity.” The TOapproach with respect to the axial and multiple transverse directions isdiscussed in International patent application serial numberPCT/IB2011/002383, titled Three Dimensional (3D) Transverse OscillationVector Velocity Ultrasound Imaging, and filed Oct. 12, 2011, theentirety of which is incorporated herein by reference.

A beamformer 108 processes the echoes, for example, by applying timedelays, weighting the channels, summing, and/or otherwise processing thereceived echoes. This includes processing the echoes and producing datafor determining a velocity spectrum for flowing structure in the axialand at least one of the azimuth or elevation directions. The illustratedbeamformer 312 also produces data for generating data for constructingimages in A-mode, B-mode, and/or other modes.

A spectral velocity estimator 110 processes the beamformed data andestimates a velocity spectrum. A first spectral velocity estimator 112estimates a velocity spectrum based on EQUATION 1. The output of thefirst spectral velocity estimator 112 is employed when the angle betweenthe velocity vector of the flowing structure and the ultrasound beam(i.e., Θ) is less than ninety (90) degrees, for example, in a range fromzero (0) to seventy (70) degrees. Angle correction can be employed forΘ>0. At Θ=90 degrees, as discussed herein, EQUATION 1 cannot be used toestimate a velocity.

A second spectral velocity estimator 114 estimates a velocity spectrumbased on the TO approach in which a pulse-echo oscillation transverse tothe ultrasound beam is made during emission or in receive processing,and a velocity spectrum estimation is made based on a correlation of thereceived signal. The second spectral velocity estimator 114 estimatesthe velocity spectrum as a function of time, like the first spectralvelocity estimator 112, but can additionally estimate a velocity even atΘ=90 degrees.

As described in greater below, the second spectral velocity estimator114 estimates a velocity spectrum, in one instance, based on auto andcross-correlation functions of the received signals (referred to hereinas a second order approach), and, in another instance, based onauto-correlation functions of the received signals, either without anaxial or without a lateral velocity component (referred to herein as afourth order approach).

Both the second order and the fourth order approaches can reliablydetermine the velocity at 90 degrees, unlike an estimation based onEQUATION 1 which, at 90 degrees, yields zero velocity. Thus, an operatorcan orient the transducer array 102 in any direction and still measurevelocity. Furthermore, the velocity range tends to be higher for thefourth order approach relative to the estimation based on EQUATION 1 asthe lateral wavelength is larger than the axial wavelength. This may bebeneficial for either keeping the pulse repetition frequency low or formaintaining a high maximum detectable velocity.

The spectral velocity estimator 110 can be implemented via aprocessor(s) (e.g., microprocessor, central processing unit or cpu,etc.) of a computing system(s) executing a computer readableinstruction(s) encoded or embedded on a computer readable storage mediumsuch as physical memory or other non-transitory medium. Additionally oralternatively, at least one instruction can be carried by a carrierwave, a signal, or other transitory or non-computer readable storagemedium.

A spectral velocity estimation selector 116 selects one of the velocityspectrums, either the velocity spectrum from the first spectral velocityestimator 112 or the velocity spectrum from the second spectral velocityestimator 114, for visual presentation. In one instance, the selectionbetween the two spectra is based on an estimated angle at the rangegate, which can be obtained using a TO estimator without additionalbeamforming. The selected velocity spectrum can be presented via adisplay 118, for example, as velocity distribution as a function oftime. In a variation, the spectral velocity estimation selector 116selects a suitable estimation approach prior to any estimation, and onlyone of the estimators 112 or 114, the estimator corresponding to theselected approach, estimates the velocity spectrum.

In one non-limiting instance, the spectral velocity estimation selector116 selects the velocity spectrum from the first spectral velocityestimator 112 or the spectral velocity estimation from the secondspectral velocity estimator 114 based on a predetermined anglethreshold. For example, in one instance, the predetermined anglethreshold is 60 degrees, and the spectral velocity estimation selector116 selects the spectral velocity estimation from the first spectralvelocity estimator 112 when the estimated angle is less than thethreshold and selects the spectral velocity estimation from the secondspectral velocity estimator 114 otherwise. Other suitable angles such as50, 70 or an angle there between are also contemplated herein. Thethreshold can be default, protocol specific, user defined, etc.

In a variation, the first spectral velocity estimator 112 is omitted,and the second spectral velocity estimator 114 estimates the velocityspectrum for all angles.

An image processor 120 processes the beamformed data, generating imagedata. For example, for B-mode, the image processor 120 processes thedata and generates a sequence of focused, coherent echo samples alongfocused scanlines of a scanplane. Other modes are also contemplatedherein. The image processor 120 may also be configured to process thescanlines to lower speckle and/or improve specular reflector delineationvia spatial compounding and/or perform other processing such as FIRfiltering, IIR filtering, etc.

A scan converter 122 scan converts the image data, generating data fordisplay, e.g., by converting the data to the coordinate system of thedisplay 118. The image data can additionally or alternatively bepresented via the display 118. Such presentation can be in aninteractive graphical user interface (GUI), which allows the user toselectively rotate, scale, and/or manipulate the displayed data. Suchinteraction can be through a mouse, a keyboard, touch-screen controls,etc.

A controller 124 controls one or more of the transmit circuitry 104 orreceive circuitry 106. Such control can be based on available modes ofoperation (e.g., spectrogram, B-mode, etc.) of the system 100. Aparticular mode can be activated by one or more signals indicative ofinput from a user via a user interface (UI) 126. The UI 126 may includeone or more input devices (e.g., a button, a knob, a slider, a touchpad, etc.) and/or one or more output devices (e.g., a display screen,lights, a speaker, etc.).

FIGS. 2, 3 and 4 illustrate examples of the spectral velocity estimator110. FIG. 2 shows an example of the first spectral velocity estimator112, and FIGS. 3 and 4 shows examples of the second spectral velocityestimator 114.

In FIG. 2, the first spectral velocity estimator 112 includes a velocitydeterminer 202, which utilizes EQUATION 1 to determine the axialvelocity of flowing structure of interest. The first spectral velocityestimator 112 further includes Fourier transform 204, which is appliedto the axial velocity to determine the spectral velocity. The axialvelocity is determined over time and visually displayed as a function oftime when the output of the first spectral velocity estimator 112 isselected by the spectral velocity estimation selector 116 (FIG. 1).

For FIGS. 3 and 4, the TO approach can yield two beams focused inparallel, namely, an in-phase (I) component and a quadrature (Q)component. This complex signal can, at one fixed depth, be described asshown in EQUATION 2:r _(sq)(i)=cos(2πf _(p) iT _(prf))exp(j2πf _(x) iT _(prf)),  EQUATION 2where i is the emission number, T_(prf) is the pulse repetition time andf_(p) is the received axial frequency, which can be defined as shown inEQUATION 3:

$\begin{matrix}{f_{p} = {\frac{2\; v_{z}}{c}{f_{0}.}}} & {{EQUATION}\mspace{14mu} 3}\end{matrix}$where f₀ is the emitted frequency, c is the speed of sound, and v_(z) isthe axial velocity component.

The temporal Hilbert transform of EQUATION 1 is shown in EQUATION 4:r _(sqh)(i)=sin(2πf _(p) iT _(prf))exp(j2πf _(x) iT _(prf)).  EQUATION 4Combining EQUATIONS 1 and 3 and using Euler's equations producesEQUATIONS 5 and 6:

$\begin{matrix}{{{r_{sq}(i)} = {\frac{1}{2}\left( {{\exp\left( {{j2\pi}\;{{iT}_{prf}\left( {f_{x} + f_{p}} \right)}} \right)} + {\exp\left( {{j2\pi}\;{{iT}_{prf}\left( {f_{x} - f_{p}} \right)}} \right)}} \right)}},{and}} & {{EQUATION}\mspace{14mu} 5} \\{{r_{sqh}(i)} = {\frac{1}{2\; j}{\left( {{\exp\left( {{j2\pi}\;{{iT}_{prf}\left( {f_{x} + f_{p}} \right)}} \right)} - {\exp\left( {{j2\pi}\;{{iT}_{prf}\left( {f_{x} - f_{p}} \right)}} \right)}} \right).}}} & {{EQUATION}\mspace{14mu} 6}\end{matrix}$Adding and subtracting EQUATIONS 5 and 6 produces two additionalequations, EQUATIONS 7 and 8:r ₁(i)=r _(sq)(i)+jr _(sqh)(i)=exp(j2πiT _(prf)(f _(x) +f _(p))),and  EQUATION 7r ₂(i)=r _(sq)(i)−jr _(sqh)(i)=exp(j2πiT _(prf)(f _(x) −f_(p))).  EQUATION 8

In FIG. 3, the second spectral velocity estimator 114 includes anautocorrelation determiner 302, which determines an autocorrelation ofthe received signal based on EQUATION 9:

$\begin{matrix}\begin{matrix}{{{R_{12}(k)} = {\sum\limits_{k = {- \infty}}^{+ \infty}\;{{r_{1}(i)}{r_{2}\left( {i + k} \right)}}}},} \\{= {\sum\limits_{k = {- \infty}}^{+ \infty}\;{{\exp\left( {{j2\pi}\;{{iT}_{prf}\left( {f_{x} + f_{p}} \right)}} \right)}\exp}}} \\{\left( {{j2\pi}\left( {i + k} \right){T_{prf}\left( {f_{x} - f_{p}} \right)}} \right)} \\{= {{\exp\left( {{j2\pi}\;{{kT}_{prf}\left( {f_{x} - f_{p}} \right)}} \right)}{\sum\limits_{k = {- \infty}}^{+ \infty}\;\exp}}} \\{\left( {{j2\pi}\;{{kT}_{prf}\left( {f_{x} + f_{p} + f_{x} - f_{p}} \right)}} \right)} \\{= {{\exp\left( {{j2\pi}\;{{kT}_{prf}\left( {f_{x} - f_{p}} \right)}} \right)}{\sum\limits_{k = {- \infty}}^{+ \infty}\;{\exp\left( {{j2\pi}\;{kT}_{prf}2\; f_{x}} \right)}}}} \\{= {{\exp\left( {{- {j2\pi}}\;{kT}_{prf}f_{p}} \right)}{\sum\limits_{k = {- \infty}}^{+ \infty}\;{{\exp\left( {{j2\pi}\mspace{11mu}{iT}_{prf}f_{x}} \right)}\exp}}}} \\{\left( {{{j2\pi}\left( {i + k} \right)}T_{prf}f_{x}} \right)} \\{= {{\exp\left( {{- {j2\pi}}\;{kT}_{prf}f_{p}} \right)}{{R_{11}(k)}.}}}\end{matrix} & {{EQUATION}\mspace{14mu} 9}\end{matrix}$When the frequency

$f_{p} = {\frac{2\; v_{z}}{c}f_{0}}$is zero, there is no axial velocity component (v_(z)=0), and thecross-correlation R₁₂(k) between the spatial in-phase and quadraturesignal directly equals the autocorrelation R₁₁(k).

The modulation of the cross-correlation function by the factorexp(j2πkT_(prf)f_(p)) can be compensated for by estimating the axialvelocity and thereby f_(p), and then multiply R₁₂(k) by the compensationfactor R_(c)(k)=exp(j2πkT_(prf)f_(p)). The axial velocity can be foundfrom a normally focused line lying between the two spatial beams andthen employing an autocorrelation estimator, rending EQUATION 10:

$\begin{matrix}{{{\hat{v}}_{z} = {\frac{{cf}_{prf}}{2\pi\; f_{0}}{\arctan\left( \frac{{\sum\limits_{i = 1}^{N_{c} - 1}\;{{y(i)}{x\left( {i - 1} \right)}}} - {{x(i)}{y\left( {i - 1} \right)}}}{{\sum\limits_{i = 1}^{N_{c} - 1}\;{{x(i)}{x\left( {i - 1} \right)}}} + {{y(i)}{y\left( {i - 1} \right)}}} \right)}}},} & {{EQUATION}\mspace{14mu} 10}\end{matrix}$where the received signal is r(i)=x(i)+jy(i) and r(i)=x(i)+jy(i).Alternatively, the velocity can be found using, for example, theapproach discussed in O. Bonnefous, P. Pesque and X. Bernard: “A newvelocity estimator for color flow mapping”, Proc. IEEE UltrasonicsSymposium, pp. 855-860, 1986, T. Loupas, J. T. Powers, R. W. Gill: Anaxial velocity estimator for ultrasound blood flow imaging, based on afull evaluation of the Doppler equation by means of a two-dimensionalautocorrelation approach, IEEE Trans. on Ultrasonics, Ferroelec. andFreq. control, vol. 43, pp. 672-688, 1995, Jensen, J A 2001, ‘A newestimator for vector velocity estimation’, IEEE Transactions onUltrasonics, Ferroelectrics and Frequency Control, vol 48, no. 4, pp.886-894 or Jensen, J A 1996, Estimation of Blood Velocities UsingUltrasound: A Signal Processing Approach. Cambridge University Press,New York.

In FIG. 3, the second spectral velocity estimator 114 further includes apower density spectrum determiner 304, which determines a velocityspectrum based on EQUATION 11:

$\begin{matrix}{{P_{11}(f)} = {\sum\limits_{k = {- \infty}}^{+ \infty}\;{{R_{11}(k)}{{\exp\left( {{- {j2\pi}}\;{fk}} \right)}.}}}} & {{EQUATION}\mspace{14mu} 11}\end{matrix}$The approach described in connection with FIG. 3 is referred to hereinas the second order approach.

In FIG. 4, the second spectral velocity estimator 114 includes anautocorrelation determiner 402, which determines an autocorrelation ofthe received signal based on EQUATION 12 or 13 (EQUATION 13 being thecomplex conjugate of EQUATION 12):R ₄₄(k)=R ₁₁(k)·R ₂₂(k),  EQUATION 12orR _(44ax)(k)=R ₁₁(k)·R* ₂₂(k),  EQUATION 13where R₁₁(k) and R₂₂(k) are respective autocorrelations R₁₁(k)=Σ_(i=−∞)^(+∞) r₁(i)r₁(i+k) and R₂₂(k)=Σ_(i=−∞) ^(+∞) r₂(i)r₂(i+k). In EQUATION12, the axial component is eliminated, and in EQUATION 13, the lateralcomponent is eliminated.

In FIG. 4, the second spectral velocity estimator 114 further includes apower density spectrum determiner 404, which determines a velocityspectrum based on EQUATION 14:

$\begin{matrix}{{{P_{44}(f)} = {\sum\limits_{k = {- \infty}}^{+ \infty}\;{{R_{44}(k)}{\exp\left( {{- {j2\pi}}\;{fk}} \right)}}}},} & {{EQUATION}\mspace{14mu} 14}\end{matrix}$The approach described in connection with FIG. 4 is referred to hereinas the fourth order approach.

FIG. 5 illustrates an example method for employing the ultrasoundimaging system discussed herein.

It is to be understood that the following acts are provided forexplanatory purposes and are not limiting. As such, one or more of theacts may be omitted, one or more acts may be added, one or more acts mayoccur in a different order (including simultaneously with another act),etc.

At 502, ultrasound imaging data is obtained using the TO approach.

At 504, the angle Θ between the velocity vector of the flowing structureand the ultrasound beam is estimated.

At 506, the estimated angle is compared with a pre-determined anglethreshold. As discussed herein, in one instance, the threshold has valuein a range between 50 and 70 degrees.

At 508, it is determined whether the estimated angle satisfies thethreshold.

If not, then at 510 a velocity determiner determines a velocity of theflowing structure based on EQUATION 1, at 512, a Fourier transform isapplied to the velocity, and at 514, the velocity distribution isdisplayed as a function of time.

If so, then at 516 either the second order power density spectrum (FIG.3) or the fourth order power density spectrum (FIG. 4) is employed todetermine velocity spectrum, and at 514 the velocity distribution isdisplayed as a function of time.

In a variation, acts 504-508 are performed after acts 510, 512 and 516,and one of the estimations is selected based on an outcome of act 508.

The methods described herein may be implemented via one or moreprocessors executing one or more computer readable instructions encodedor embodied on computer readable storage medium such as physical memorywhich causes the one or more processors to carry out the various actsand/or other functions and/or acts. Additionally or alternatively, theone or more processors can execute instructions carried by transitorymedium such as a signal or carrier wave.

The application has been described with reference to variousembodiments. Modifications and alterations will occur to others uponreading the application. It is intended that the invention be construedas including all such modifications and alterations, including insofaras they come within the scope of the appended claims and the equivalentsthereof.

What is claimed is:
 1. An ultrasound imaging system, comprising: a transducer array that emits an ultrasound beam and produces at least one transverse pulse-echo field that oscillates in a direction transverse to the emitted ultrasound beam and that receive echoes produced in response thereto; and a spectral velocity estimator that determines a power density spectrum for a flowing structure, which flows at an angle of 90 degrees and flows at angles less than 90 degrees with respect to the emitted ultrasound beam, based on the received echoes.
 2. The system of claim 1, wherein the velocity processor determines the power density spectrum based on an autocorrelation of the echoes.
 3. The system of claim 2, wherein the velocity processor determines the autocorrelation based on a cross-correlation of between spatial in-phase and quadrature signals.
 4. The system of claim 3, wherein the autocorrelation equals the cross-correlation in response to an axial velocity component equal to zero.
 5. The system of claim 3, wherein a modulation of the cross-correlation is compensated for by multiplying the cross-correlation by a compensation factor.
 6. The system of claim 5, wherein the compensation factor is based on an axial velocity estimated from a normally focused line lying between two spatial beams and employing an autocorrelation estimator.
 7. The system of claim 2, wherein the velocity processor determines the autocorrelation based on an autocorrelation of spatial in-phase signals and an autocorrelation of quadrature signals.
 8. The system of claim 7, wherein the autocorrelation does not include an axial velocity component.
 9. The system of claim 2, wherein the velocity processor determines the autocorrelation based on an autocorrelation of spatial in-phase signals and a complex conjugate of an autocorrelation of quadrature signals.
 10. The system of claim 9, wherein the autocorrelation does not include a lateral velocity component.
 11. The system of claim 2, wherein the velocity processor determines the power density spectrum based on the autocorrelation in response to an angle between a velocity vector of the flowing structure and the ultrasound beam being greater than sixty degrees.
 12. The system of claim 11, wherein the velocity processor determines the power density spectrum based on a measured frequency in response to the angle being less than sixty degrees.
 13. The system of claim 1, further comprising: a display that visually presents the power density spectrum.
 14. A method, comprising: receiving echoes in response to emitting an ultrasound beam and at least one transverse pulse-echo field that oscillates in a direction transverse to the emitted ultrasound beam; and determining a power density spectrum for flowing structure, which flows at an angle of 90 degrees and flows at angles less than 90 degrees with respect to the emitted ultrasound, beam based on the received echoes.
 15. The method of claim 14, further comprising: determining the power density spectrum based on an autocorrelation of the echoes.
 16. The method of claim 14, further comprising: determining the autocorrelation based on a cross-correlation of between spatial in-phase and quadrature signals.
 17. The method of claim 14, further comprising: determining the autocorrelation based on an autocorrelation of spatial in-phase signals and an autocorrelation of quadrature signals.
 18. The method of claim 14, further comprising: determining the autocorrelation based on an autocorrelation of spatial in-phase signals and a complex conjugate of an autocorrelation of quadrature signals.
 19. The method of claim 14, further comprising: determining the power density spectrum based on the autocorrelation in response to an angle between a velocity vector of the flowing structure and the ultrasound beam being greater than sixty degrees.
 20. The method of claim 19, further comprising: determining the power density spectrum based on a measured frequency in response to the angle being less than sixty degrees.
 21. The system of claim 13, further comprising: visually presenting the power density spectrum as a function of time.
 22. A spectral velocity estimator, comprising: a first spectral velocity estimator that estimates a velocity spectrum in response to an angle between a velocity vector and the ultrasound beam being less than a first threshold angle, which does not include ninety degrees, wherein the first spectral velocity estimator estimates the velocity spectrum based on a measured frequency; and a second spectral velocity estimator that estimates the velocity spectrum in response to the angle between the velocity vector and the ultrasound beam being greater than the first threshold angle, which includes ninety degrees, wherein the second spectral velocity estimator estimates the velocity spectrum based on a correlation of received echoes. 